Pemanfaatan Artificial Neural Network Dengan Teknik Backpropagation Untuk Prakiraan Cuaca Harian
Abstract
Berdasarkan data dari Badan Nasional Penanggulangan Bencana (BNPB), selama tahun 2022 saja, telah terjadi 3.054 bencana dengan korban meninggal sampai 392 orang, dengan jumlah kejadian cuaca ekstrim dapat mencapai 931 kejadian. Untuk mengantisipasi dampak yang ditimbulkan oleh cuaca ekstrim, BMKG mengeluarkan prakiraan cuaca, agar masyarakat siap, ketika cuaca ekstrim itu datang. Aplikasi penggunaan teknik Artificial Neural Network (ANN) pada prakiraan cuaca yang sangat berdampak, meningkatkan kemampuan untuk menyelami luasnya big data dalam mendapatkan informasi yang diperlukan, sebagai pembantu yang tepat bagi prakiraan dan pembuatan kebijakan. Data yang digunakan pada penelitian ini adalah data unsur-unsur cuaca, seperti tekanan, suhu udara, kelembaban, arah dan kecepatan angin, serta curah hujan, yang didapatkan dari Stasiun Meteorologi Radin Inten II Lampung. Data observasi memiliki kerapatan data per 1 jam, dengan rentang waktu selama 5 tahun yaitu dari 01 Januari 2018 – 31 Desember 2022. Metode yang dipakai dalam penelitian ini adalah Backpropagation Neural Network (BPNN). Hasil penelitian menunjukkan BPNN dapat memprakirakan hujan terklasifikasi dengan baik dibandingkan metode lainnya.
Keywords
References
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DOI: http://dx.doi.org/10.26623/transformatika.v21i2.6937
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